Triglyceride-glucose index is associated with myocardial ischemia and poor prognosis in patients with ischemia and no obstructive coronary artery disease.

BACKGROUND: Ischemia and no obstructive coronary artery disease (INOCA) is increasingly recognized and associated with poor outcomes. The triglyceride-glucose (TyG) index is a reliable alternative measure of insulin resistance significantly linked to cardiovascular disease and adverse prognosis. We investigated the association between the TyG index and myocardial ischemia and the prognosis in INOCA patients. METHODS: INOCA patients who underwent both coronary angiography and myocardial perfusion imaging (MPI) were included consecutively. All participants were divided into three groups according to TyG tertiles (T1, T2, and T3). Abnormal MPI for myocardial ischemia in individual coronary territories was defined as summed stress score (SSS) ≥ 4 and summed difference score (SDS) ≥ 2. SSS refers to the sum of all defects in the stress images, and SDS is the difference of the sum of all defects between the rest images and stress images. All patients were followed up for major adverse cardiac events (MACE). RESULTS: Among 332 INOCA patients, 113 (34.0%) had abnormal MPI. Patients with higher TyG index had a higher rate of abnormal MPI (25.5% vs. 32.4% vs. 44.1%; p = 0.012). Multivariate logistic analysis showed that a high TyG index was significantly correlated with abnormal MPI in INOCA patients (OR, 1.901; 95% CI, 1.045-3.458; P = 0.035). During the median 35 months of follow-up, 83 (25%) MACE were recorded, and a higher incidence of MACE was observed in the T3 group (T3 vs. T2 vs. T1: 36.9% vs. 21.6% vs. 16.4%, respectively; p = 0.001). In multivariate Cox regression analysis, the T3 group was significantly associated with the risk of MACE compared to the T1 group (HR, 2.338; 95% CI 1.253-4.364, P = 0.008). CONCLUSION: This study indicates for the first time that the TyG index is significantly associated with myocardial ischemia and poor prognosis among INOCA patients.

Cost prediction for ischemic heart disease hospitalization: Interpretable feature extraction using network analysis.

OBJECTIVES: Ischemic heart disease (IHD) is a significant contributor to global mortality and disability, imposing a substantial social and economic burden on individuals and healthcare systems. To enhance the efficient allocation of medical resources and ultimately benefit a larger population, accurate prediction of healthcare costs is crucial. METHODS: We developed an interpretable IHD hospitalization cost prediction model that integrates network analysis with machine learning. Specifically, our network-enhanced model extracts explainable features by leveraging a diagnosis-procedure concurrence network and advanced graph kernel techniques, facilitating the capture of intricate relationships between medical codes. RESULTS: The proposed model achieved an R2 of 0.804 ± 0.008 and a root mean square error (RMSE) of 17,076 ± 420 CNY on the temporal validation dataset, demonstrating comparable performance to the model employing less interpretable code embedding features (R2: 0.800 ± 0.008; RMSE: 17,279 ± 437 CNY) and the hybrid graph isomorphism network (R2: 0.802 ± 0.007; RMSE: 17,249 ± 387 CNY). The interpretation of the network-enhanced model assisted in pinpointing specific diagnoses and procedures associated with higher hospitalization costs, including acute kidney injury, permanent atrial fibrillation, intra-aortic balloon bump, and temporary pacemaker placement, among others. CONCLUSION: Our analysis results demonstrate that the proposed model strikes a balance between predictive accuracy and interpretability. It aids in identifying specific diagnoses and procedures associated with higher hospitalization costs, underscoring its potential to support intelligent management of IHD.

Meta-analysis of the association between interleukin-17 and ischemic cardiovascular disease.

BACKGROUND: Interleukin-17 (IL-17) has been hypothesized to be involved in ischemic cardiovascular disease (ICVD). However, the association of IL-17 with ICVD remained unclear. The aim of this study was to systematically analyze the available evidence regarding the association between IL-17 and ICVD. METHODS: We searched the PubMed, Web of Science, Cochrane Library, and Embase databases up to October 2023 to identify publications on the association between IL-17 and ICVD. The merged results were analyzed using a random effects model for meta-analysis and subgroup analysis. RESULTS: A total of 955 publications were initially identified in our search and screened; six studies were eventually included in the analysis. The average age of study participants was 60.3 ± 12.6 years and 65.5% were men. There was a high degree of heterogeneity among studies. The results showed that IL-17 level were higher in the case group than those in the control group (standardized mean difference, SMD = 1.60, 95% confidence interval (95% CI): 0.53-2.66, P = 0.003). In sensitivity analysis, the merged results showed good robustness. Additionally, subgroup analysis showed that race and ethnicity, sample size, and detection methods were significant factors influencing heterogeneity in the published studies. CONCLUSION: Our finding revealed that increased IL-17 level contributed to the development of ICVD, suggesting IL-17 as a potential risk marker. Further research is needed to establish IL-17 as a therapeutic biomarker of ICVD.

Contributions of elevated CRP, hyperglycaemia, and type 2 diabetes to cardiovascular risk in the general population: observational and Mendelian randomization studies.

OBJECTIVE: To investigate the contributions of low-grade inflammation measured by C-reactive protein (CRP), hyperglycaemia, and type 2 diabetes to risk of ischemic heart disease (IHD) and cardiovascular disease (CVD) death in the general population, and whether hyperglycaemia and high CRP are causally related. RESEARCH DESIGN AND METHODS: Observational and bidirectional, one-sample Mendelian randomization (MR) analyses in 112,815 individuals from the Copenhagen General Population Study and the Copenhagen City Heart Study, and bidirectional, two-sample MR with summary level data from two publicly available consortia, CHARGE and MAGIC. RESULTS: Observationally, higher plasma CRP was associated with stepwise higher risk of IHD and CVD death, with hazard ratios and 95% confidence intervals (95%CI) of 1.50 (1.38, 1.62) and 2.44 (1.93, 3.10) in individuals with the 20% highest CRP concentrations. The corresponding hazard ratios for elevated plasma glucose were 1.10 (1.02, 1.18) and 1.22 (1.01, 1.49), respectively. Cumulative incidences of IHD and CVD death were 365% and 592% higher, respectively, in individuals with both type 2 diabetes and plasma CRP ≥ 2 mg/L compared to individuals without either. Plasma CRP and glucose were observationally associated (ß-coefficient: 0.02 (0.02, 0.03), p = 3 × 10- 20); however, one- and two-sample MR did not support a causal effect of CRP on glucose (-0.04 (-0.12, 0.32) and - 0.03 (-0.13, 0.06)), nor of glucose on CRP (-0.01 (-0.08, 0.07) and - 0.00 (-0.14, 0.13)). CONCLUSIONS: Elevated concentrations of plasma CRP and glucose are predictors of IHD and CVD death in the general population. We found no genetic association between CRP and glucose, or vice versa, suggesting that lowering glucose pharmacologically does not have a direct effect on low-grade inflammation.

Risk Stratification Using Right Ventricular Longitudinal Strain Ratio Derived from 13N-Ammonia PET in Patients with Ischemic Heart Disease.

Purpose To investigate whether right ventricular (RV) myocardial strain ratio (RVMSR) assessed using nitrogen 13 ammonia (13N-NH3) PET can predict cardiovascular events in patients with ischemic heart disease (IHD). Materials and Methods This retrospective study included 480 consecutive patients (mean age, 66 years ± 12 [SD]; 334 males and 146 females) with IHD who underwent 13N-NH3 PET. RVMSR was defined as the ratio of RV strain during stress to that at rest. The primary end point was major adverse cardiac events (MACEs), defined as cardiac death or heart failure hospitalization. The ability of RVMSR to predict MACE was assessed using receiver operating characteristic (ROC) curve and Kaplan-Meier analyses. Cox proportional hazards regression analysis was used to calculate hazard ratios (HRs) with 95% CIs. Results ROC curve analysis identified a sensitivity and specificity of 84% and 82%, respectively, for predicting MACE from RVMSR. Patients with reduced RVMSR (<110.2) displayed a significantly higher rate of MACE than those with a preserved RVMSR (34 of 240 vs four of 240; P < .001). Cox proportional hazards regression analysis of imaging parameters, including myocardial flow reserve, indicated that RVMSR was an independent predictor of MACE (HR, 0.94 [95% CI: 0.92, 0.97]; P < .001). Conclusion RVMSR was an independent predictor of MACE and has potential to aid in the risk stratification of patients with IHD. Keywords: Right Ventricular Myocardial Strain Ratio, Myocardial Flow Reserve, Ischemic Heart Disease, 13N-Ammonia Positron Emission Tomography Supplemental material is available for this article. © RSNA, 2024.

Forward problem of electrocardiography based on cardiac source vector orientations.

To localize the unusual cardiac activities non-invasively, one has to build a prior forward model that relates the heart, torso, and detectors. This model has to be constructed to mathematically relate the geometrical and functional activities of the heart. Several methods are available to model the prior sources in the forward problem, which results in the lead field matrix generation. In the conventional technique, the lead field assumed the fixed prior sources, and the source vector orientations were presumed to be parallel to the detector plane with the unit strength in all directions. However, the anomalies cannot always be expected to occur in the same location and orientation, leading to misinterpretation and misdiagnosis. To overcome this, the work proposes a new forward model constructed using the VCG signals of the same subject. Furthermore, three transformation methods were used to extract VCG in constructing the time-varying lead fields to steer to the orientation of the source rather than just reconstructing its activities in the inverse problem. In addition, the unit VCG loop of the acute ischemia patient was extracted to observe the changes compared to the normal subject. The abnormality condition was achieved by delaying the depolarization time by 15ms. The results involving the unit vectors of VCG demonstrated the anisotropic nature of cardiac source orientations, providing information about the heart's electrical activity.

The role of beat-by-beat cardiac features in machine learning classification of ischemic heart disease (IHD) in magnetocardiogram (MCG).

Cardiac electrical changes associated with ischemic heart disease (IHD) are subtle and could be detected even in rest condition in magnetocardiography (MCG) which measures weak cardiac magnetic fields. Cardiac features that are derived from MCG recorded from multiple locations on the chest of subjects and some conventional time domain indices are widely used in Machine learning (ML) classifiers to objectively distinguish IHD and control subjects. Most of the earlier studies have employed features that are derived from signal-averaged cardiac beats and have ignored inter-beat information. The present study demonstrates the utility of beat-by-beat features to be useful in classifying IHD subjects (n = 23) and healthy controls (n = 75) in 37-channel MCG data taken under rest condition of subjects. The study reveals the importance of three features (out of eight measured features) namely, the field map angle (FMA) computed from magnetic field map, beat-by-beat variations of alpha angle in the ST-T region and T wave magnitude variations in yielding a better classification accuracy (92.7 %) against that achieved by conventional features (81 %). Further, beat-by-beat features are also found to augment the accuracy in classifying myocardial infarction (MI) Versus control subjects in two public ECG databases (92 % from 88 % and 94 % from 77 %). These demonstrations summarily suggest the importance of beat-by-beat features in clinical diagnosis of ischemia.

Predictive value of plaque characteristics for identification of lesions causing ischemia.

BACKGROUND: Functional assessment using fractional flow reserve (FFR) and anatomical assessment using optical coherence tomography (OCT) are used in clinical practice for patients with intermediate coronary stenosis. Moreover, coronary computed tomography angiography (CTA) is a common noninvasive imaging technique for evaluating suspected coronary artery disease before being referred for angiography. This study aimed to investigate the association between FFR and plaque characteristics assessed using coronary CTA and OCT for intermediate coronary stenosis. METHODS: Based on a prospective multicenter registry, 159 patients having 339 coronary lesions with intermediate stenosis were included. All patients underwent coronary CTA before being referred for coronary angiography, and both FFR measurements and OCT examinations were performed during angiography. A stenotic lesion identified with FFR ≤0.80 was deemed diagnostic of an ischemia-causing lesion. The predictive value of plaque characteristics assessed using coronary CTA and OCT for identifying lesions causing ischemia was analyzed. RESULTS: Stenosis severity and plaque characteristics on coronary CTA and OCT differed between lesions that caused ischemia and those that did not. In multivariate analysis, low attenuation plaque on coronary CTA (odds ratio [OR]=2.78; P=0.038), thrombus (OR=5.13; P=0.042), plaque rupture (OR=3.25; P=0.017), and intimal vasculature on OCT (OR=2.57; P=0.012) were independent predictors of ischemic lesions. Increasing the number of these plaque characteristics offered incremental improvement in predicting the lesions causing ischemia. CONCLUSIONS: Comprehensive anatomical evaluation of coronary stenosis may provide additional supportive information for predicting the lesions causing ischemia.

Myocardial motion in acute ischemia: revealing invisible deformation by echocardiography.

Echocardiography has been used clinically to assess regional myocardial wall motion for the diagnosis of acute myocardial ischemia or stress-induced ischemia, but it is often difficult to distinguish hypokinetic motion from normal motion. Myocardial wall motion is affected by loading conditions as well as intrinsic contractility, making it challenging to define a normal range of wall motion. Therefore, hypokinesis is usually diagnosed by comparing target areas with other areas of myocardium considered normal (relative hypokinesis). Myocardial strain analysis by tissue Doppler echocardiography and speckle-tracking echocardiography has enabled objective and quantitative evaluation of regional myocardial wall motion. Peak systolic strain decreases during acute ischemia, but subtle and invisible myocardial motion, such as early systolic lengthening (ESL) and postsystolic shortening (PSS), also occurs, and the analysis of these subtle motions can improve the diagnostic accuracy of ischemia. However, the diagnosis of ischemic myocardium by strain analysis is not widely performed in clinical practice at this time due to several limitations. This article reviews the features of myocardial motion during acute ischemia, the mechanisms of ESL and PSS, the diagnosis of ischemic myocardium using strain analysis, and current approaches and future challenges to overcome the limitations in the detection of relative hypokinesis. This article also explains the use of ESL and PSS to detect myocardial ischemic memory that remains after brief ischemia.

Machine learning to identify a composite indicator to predict cardiac death in ischemic heart disease.

BACKGROUND: Machine learning (ML) employs algorithms that learn from data, building models with the potential to predict events by aggregating a large number of variables and assessing their complex interactions. The aim of this study is to assess ML potential in identifying patients with ischemic heart disease (IHD) at high risk of cardiac death (CD). METHODS: 3987 (mean age 68 ± 11) hospitalized IHD patients were enrolled. We implemented and compared various ML models and their combination into ensembles. Model output constitutes a new ML indicator to be employed for stratification. Primary variable importance was assessed with ablation tests. RESULTS: An ensemble classifier combining three ML models achieved the best performance to predict CD (AUROC of 0.830, F1-macro of 0.726). ML indicator use through Cox survival analysis outperformed the 18 variables individually, producing a better stratification compared to standard multivariate analysis (improvement of ∼20%). Patients in the low risk group defined through ML indicator had a significantly higher survival (88.8% versus 29.1%). The main variables identified were Dyslipidemia, LVEF, Previous CABG, Diabetes, Previous Myocardial Infarction, Smoke, Documented resting or exertional ischemia, with an AUROC of 0.791 and an F1-score of 0.674, lower than that of 18 variables. Both code and clinical data are freely available with this article. CONCLUSION: ML may allow a faster, low-cost and reliable evaluation of IHD patient prognosis by inclusion of more predictors and identification of those more significant, improving outcome prediction towards the development of precision medicine in this clinical field.

Low HDL cholesterol and the eNOS Glu298Asp polymorphism are associated with inducible myocardial ischemia in patients with suspected stable coronary artery disease.

BACKGROUND: The endothelial nitric oxide synthase (eNOS) gene deficiency is known to cause impaired coronary vasodilating capability in animal models. In the general clinical population, the eNOS gene polymorphisms, able to affect eNOS activity, were associated with cardiometabolic risk features and prevalence of coronary artery disease (CAD). AIM: To investigate the association of eNOS Glu298Asp gene polymorphism, cardiometabolic profile, obstructive CAD and inducible myocardial ischemia in patients with suspected stable CAD. METHODS: A total of 506 patients (314 males; mean age 62 ± 9 years) referred for suspected CAD was enrolled. Among these, 325 patients underwent stress ECG or cardiac imaging to assess the presence of inducible myocardial ischemia and 436 patients underwent non-invasive computerized tomography or invasive coronary angiography to assess the presence of obstructive CAD. Clinical characteristics and blood samples were collected for each patient. RESULTS: In the whole population, 49.6% of patients were homozygous for the Glu298 genotype (Glu/Glu), 40.9% heterozygotes (Glu/Asp) and 9.5% homozygous for the 298Asp genotype (Asp/Asp). Obstructive CAD was documented in 178/436 (40.8%) patients undergoing coronary angiography while myocardial ischemia in 160/325 (49.2%) patients undergoing stress testing. Patients with eNOS Asp genotype (Glu/Asp + Asp/Asp) had no significant differences in clinical risk factors and in circulating markers. Independent predictors of obstructive CAD were age, gender, obesity, and low HDL-C. Independent predictors of myocardial ischemia were gender, obesity, low HDL-C and Asp genotype. In the subpopulation in which both stress tests and coronary angiography were performed, the Asp genotype remained associated with increased myocardial ischemia risk after adjustment for obstructive CAD. CONCLUSION: In this population, low-HDL cholesterol was the only cardiometabolic risk determinant of obstructive CAD. The eNOS Glu298Asp gene polymorphism was significantly associated with inducible myocardial ischemia independently of other risk factors and presence of obstructive CAD.

Diagnosing Coronary Artery Disease in the Patient Presenting with Stable Ischemic Heart Disease: The Role of Anatomic versus Functional Testing.

There are unique advantages and disadvantages to functional versus anatomic testing in the work-up of patients who present with symptoms suggestive of obstructive coronary artery disease. Evaluation of these individuals starts with an assessment of pre-test probability, which guides subsequent testing decisions. The choice between anatomic and functional testing depends on this pre-test probability. In general, anatomic testing has particular utility among younger individuals and women; while functional testing can be helpful to rule-in ischemia and guide revascularization decisions. Ultimately, selection of the most appropriate test should be individualized to the patient and clinical scenario.

Optimal Medical Therapy for Stable Ischemic Heart Disease: Focus on Anti-anginal Therapy.

Chronic coronary disease (CCD) is a major cause of morbidity and mortality worldwide. The most common symptom of CCD is exertional angina pectoris, a discomfort in the chest that commonly occurs during activities of daily life. Patients are dismayed by recurring episodes of angina and seek medical help in preventing or minimizing episodes. Angina occurs when the coronary arteries are unable to supply sufficient blood flow to the cardiac muscle to meet the metabolic needs of the left ventricular myocardium. While lifestyle changes and aggressive risk factor modification play a critical role in the management of CCD, management of angina usually requires pharmacologic therapy. Medications such as beta-blockers, calcium channel blockers, nitrates, ranolazine, and others ultimately work to improve the mismatch between myocardial blood flow and metabolic demand. This manuscript briefly describes the pathophysiologic basis for symptoms of angina, and how currently available anti-anginal therapies contribute to preventing or minimize the occurrence of angina.

The Pathophysiologic Basis of Managing Chronic Atherosclerotic Cardiovascular Disease.

Chronic coronary heart disease encompasses a broad spectrum of disorders that range in severity from trivial to imminently life-threatening. The primary care physician encounters coronary disease at all stages. The number of available diagnostic and therapeutic options for evaluating and treating coronary disease is vast, presenting a complex selection strategy challenge when making choices for the individual patient. The primary care physician is responsible to tailor evaluation and management strategies to each individual patient based on his/her particular disease characteristics. There are many categories of diagnostic studies and therapeutic interventions that have been shown at the population level in clinical trials to improve patient outcomes. Blindly applying the findings of all demonstrated studies and therapies to a patient with coronary disease would saddle him/her with an unsustainable burden of diagnostic tests and therapies. The core principle of the approach outlined in this article is to tailor diagnostic and therapeutic choices to the operative pathophysiology that drives a particular patient's disorder. This introductory article is intended to provide a conceptual framework for studying and applying the specialized topics discussed in the articles that follow.

Ischemic Heart Disease in Women.

This review synthesizes the current understanding of ischemic heart disease in women, briefly discussing differences in risk factors, presentation, and treatment. We have underscored the unique clinical phenotype of IHD in women with a higher prevalence of ischemia with non-obstructive coronary arteries. Further research is needed to elucidate the complexities of ischemic heart disease in women, understand the discordance between ischemic burden and clinical symptoms, and optimize treatment strategies.

Medical Decision-Making and Revascularization in Ischemic Cardiomyopathy.

Ischemic cardiomyopathy (ICM) is the most common underlying etiology of heart failure in the United States and is a significant contributor to deaths due to cardiovascular disease worldwide. The diagnosis and management of ICM has advanced significantly over the past few decades, and the evidence for medical therapy in ICM is both compelling and robust. This contrasts with evidence for coronary revascularization, which is more controversial and favors surgical approaches. This review will examine landmark clinical trial results in detail as well as provide a comprehensive overview of the current epidemiology, diagnostic approaches, and management strategies of ICM.

Association between preoperative frailty and myocardial injury after noncardiac surgery in geriatric patients: study protocol for a prospective, multicentre, real-world observational, cohort trial.

INTRODUCTION: Frailty has become a worldwide health burden that has a large influence on public health and clinical practice. The incidence of frailty is anticipated to increase as the ageing population increases. Myocardial injury after noncardiac surgery (MINS) is associated with short-term and long-term mortality. However, the incidence of MINS in frail geriatric patients is unknown. METHODS AND ANALYSIS: This prospective, multicentre, real-world observational cohort study will be conducted at 18 designated centres in China from January 2023 to December 2024, with an anticipated sample size of 856 patients aged 65 years and older who are scheduled to undergo noncardiac surgery. The primary outcome will be the incidence of MINS. MINS is defined as a fourth-generation plasma cardiac troponin T (cTnT) concentration ≥ 0.03 ng/mL exhibited at least once within 30 days after surgery, with or without symptoms of myocardial ischaemia. All data will be collected via electronic data acquisition. DISCUSSION: This study will explore the incidence of MINS in frail patients. The characteristics, predictive factors and 30-day outcomes of MINS in frail patients will be further investigated to lay the foundation for identifying clinical interventions. CLINICAL TRIAL REGISTRATION: https://beta. CLINICALTRIALS: gov/study/NCT05635877 , NCT05635877.